Reinforcement Learning
Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle
Simon S. Du, Yuping Luo, Ruosong Wang, Hanrui Zhang
Neural Information Processing Systems http://nips.cc/
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment
Felix Leibfried, Sergio Pascual-Dรญaz, Jordi Grau-Moya
Neural Information Processing Systems http://nips.cc/
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design -- Supplementary Materials 1 Hyperparameters 1 1.1 GROOVE 2
Agent hyperparameters were based on tuned A2C agents, before being fine-tuned with LPG.
HubRouter: Learning Global Routing via Hub Generation and Pin-hub Connection
Global Routing (GR) is a core yet time-consuming task in VLSI systems.
Large Language Models Are Semi-Parametric Reinforcement Learning Agents
As declared by Seifert et al. [1997], the episodic memory of the experiences from past episodes plays a crucial role in the complex decision-making processes of human [Suddendorf and Corballis, 2007]. By recollecting the experiences from past episodes, the human can learn from success to repeat it and learn from failure to avoid it.